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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Active Learning Accelerated Discovery of Stable Iridium Oxide Polymorphs for the Oxygen Evolution Reaction

The discovery of high-performing and stable materials for sustainable energy applications is a pressing goal in catalysis and materials science. Understanding the relationship between a material’s structure and functionality is an important step in the process, such that viable polymorphs for a given chemical composition need to be identified. Machine-learning-based surrogate models have the potential to accelerate the search for polymorphs that target specific applications. Herein, we report a readily generalizable active-learning (AL) accelerated algorithm for identification of electrochemically stable iridium oxide polymorphs of IrO 2 and IrO 3 . The search is coupled to a subsequent analysis of the electrochemical stability of the discovered structures for the acidic oxygen evolution reaction (OER). Structural candidates are generated by identifying all 956 structurally unique AB2 and AB3 prototypes in existing materials databases (more than 38000). Next, using an active learning approach, we find 196 IrO 2 polymorphs within the thermodynamic amorphous synthesizability limit and reaffirm the global stability of the rutile structure. We find 75 synthesizable IrO 3 polymorphs and report a previously unknown FeF 3 -type structure as the most stable, termed α-IrO 3 . To test the algorithms performance, we compare to a random search of the candidate space and report at least a 2-fold increase in the rate of discovery. Additionally, the AL approach can acquire the most stable polymorphs of IrO 2 and IrO 3 with fewer than 30 density functional theory optimizations. Analysis of the structural properties of the discovered polymorphs reveals that octahedral local coordination environments are preferred for nearly all low-energy structures. Subsequent Pourbaix Ir–H 2 O analysis shows that α-IrO3 is the globally stable solid phase under acidic OER conditions and supersedes the stability of rutile IrO 2 . Calculation of theoretical OER surface activities reveal ideal weaker binding of the OER intermediates on α-IrO 3 than on any other considered iridium oxide. We emphasize that the proposed AL algorithm can be easily generalized to search for any binary metal oxide structure with a defined stoichiometry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Physically Informed Machine Learning Prediction of Electronic Density of States

The electronic structure of a material, such as its density of states (DOS), provides key insights into its physical and functional properties and serves as a valuable source of high-quality features for many materials screening and discovery workflows. Still, the computational cost of calculating the DOS, most commonly with density functional theory (DFT), becomes prohibitive for meeting high-fidelity or high-throughput requirements, necessitating a cheaper but sufficiently accurate surrogate. To fulfill this demand, we develop a general machine learning method based on graph neural networks for predicting the DOS purely from atomic positions, six orders of magnitude faster than DFT. This approach can effectively use large materials databases and be applied generally across the entire periodic table to materials classes of arbitrary compositional and structural diversity. We furthermore devise a highly adaptable scheme for physically informed learning which encourages the DOS prediction to favor physically reasonable solutions defined by any set of desired constraints. This functionality provides a means for ensuring that the predicted DOS is reliable enough to be used as an input to downstream materials screening workflows to predict more complex functional properties, which rely on accurate physical features.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Defect Diffusion Graph Neural Networks for Materials Discovery in High-Temperature Energy Applications

Here, the migration of crystallographic defects dictates material properties and performance for a plethora of technological applications. Density functional theory (DFT)-based nudged elastic band (NEB) calculations are a powerful computational technique for predicting defect migration activation energy barriers, yet they become prohibitively expensive for high-throughput screening of defect diffusivities. Without introducing hand-crafted (i.e., chemistry- or structure-specific) descriptors, we propose a generalized deep learning approach to train surrogate models for NEB energies of vacancy migration by hybridizing graph neural networks with transformer encoders and simply using pristine host structures as input. With sufficient training data, computationally efficient and simultaneous inference of vacancy defect thermodynamics and migration activation energies can be obtained to compute temperature-dependent vacancy diffusivities and to down-select candidates for more thorough DFT analysis or experiments. Thus, as we specifically demonstrate for potential water-splitting materials, candidates with desired defect thermodynamics, kinetics, and host stability properties can be more rapidly targeted from open-source databases of experimentally validated or hypothetical materials.

14 SOLAR ENERGY↗
DOE OSTI2021

Thermal Energy Transport in Oxide Nuclear Fuel

To efficiently capture the energy of the nuclear bond, advanced nuclear reactor concepts seek solid fuels that must withstand unprecedented temperature and radiation extremes. In these advanced fuels, thermal energy transport under irradiation is directly related to reactor performance as well as reactor safety. The science of thermal transport in nuclear fuel is a grand challenge as a result of both computational and experimental complexities. Here we provide a comprehensive review of thermal transport research on two actinide oxides: one currently in use in commercial nuclear reactors, uranium dioxide (UO 2 ), and one advanced fuel candidate material, thorium dioxide (ThO 2 ). In both materials, heat is carried by lattice waves or phonons. Crystalline defects caused by fission events effectively scatter phonons and lead to a degradation in fuel performance over time. Bolstered by new computational and experimental tools, researchers are now developing the foundational work necessary to accurately model and ultimately control thermal transport in advanced nuclear fuels. We begin by reviewing research aimed at understanding thermal transport in perfect single crystals. The absence of defects enables studies that focus on the fundamental aspects of phonon transport. Next, we review research that targets defect generation and evolution. Here the focus is on ion irradiation studies used as surrogates for damage caused by fission products. We end this review with a discussion of modeling and experimental efforts directed at predicting and validating mesoscale thermal transport in the presence of irradiation defects. While efforts in these research areas have been robust, challenging work remains in developing holistic tools to capture and predict thermal energy transport across widely varying environmental conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Data Generation for Machine Learning Interatomic Potentials and Beyond

The field of data-driven chemistry is undergoing an evolution, driven by innovations in machine learning models for predicting molecular properties and behavior. Recent strides in ML-based interatomic potentials have paved the way for accurate modeling of diverse chemical and structural properties at the atomic level. The key determinant defining MLIP reliability remains the quality of the training data. A paramount challenge lies in constructing training sets that capture specific domains in the vast chemical and structural space. This Review navigates the intricate landscape of essential components and integrity of training data that ensure the extensibility and transferability of the resulting models. We delve into the details of active learning, discussing its various facets and implementations. We outline different types of uncertainty quantification applied to atomistic data acquisition and the correlations between estimated uncertainty and true error. The role of atomistic data samplers in generating diverse and informative structures is highlighted. Furthermore, we discuss data acquisition via modified and surrogate potential energy surfaces as an innovative approach to diversify training data. The Review also provides a list of publicly available data sets that cover essential domains of chemical space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Liquid–Liquid Equilibrium Prediction in Fast Pyrolysis Bio-Oil Systems: A Framework for Incorporating Bio-Oil Complexity

The study of mixtures of bio-oil, water and organic solvents in different proportions can serve as a cost-effective analysis of its content due to the formation of immiscible phases. This manuscript attempts to replicate experimentally determined partition coefficients (K OW ) of relevant species present in fast pyrolysis bio-oil (FPBO). A commercial flowsheeting simulator with surrogate bio-oil model representation is used. Concurrently, pyrolytic lignins in FPBO (‘pyrolignin’) do not have an agreed-upon structural representation, and the literature is ripe with wide variations of said representations. Thus, during the description of FPBO, this pyrolignin fraction was modeled using 20 possible structures (phenolic dimers to tetramers), with the goal of determining the structures for which the experimental data are best described. Two cases were considered: Case 1 normalized the reported experimental mass balance, while Case 2 included the unreported fraction in the mass balance to the total pyroligin. Please, add here a comment on the prediction of the Water oil equilibrium. The best KOW predictions for levoglucosan (LVG) were obtained when the system was modeled with no pyrolignin, presenting an MRE under 10% for both systems WO and BO. Among the possible structures, D2 (dimer), F1 (trimer) and I1, and I3 (tetramers) presented MRE ≤ 13% for both cases.

09 BIOMASS FUELS↗
DOE OSTI2025

Chemical Diversity of Oligomers in Biomass Fast Pyrolysis Oils, Part 2: Heavy Lignin-Derived Molecules and Highly Dehydrated Sugars from Dichloromethane-Insoluble Pyrolytic Lignin

Here, this paper, the second in a series, investigates the water-insoluble, dichloromethane (DCM)-insoluble residue of BTG pyrolysis oil, also known in the literature as high-molecular-weight pyrolytic lignin (HMW-PL). HMW-PL accounts for 9.2 wt % of the original bio-oil, which is known to increase upon aging and contribute to coke formation during bio-oil upgrading. Understanding its composition is crucial for managing pyrolysis oil during the processing. The HMW-PL was fractionated using a silica gel column with solvents of increasing polarity: ethyl acetate (EA), acetone (AC), isopropanol (ISO), and methanol (MeOH), yielding 49.2, 19.9, 8.2, and 8.1 wt %, respectively. Each subfraction was characterized by UV-fluorescence, FTIR, HSQC NMR, and (−)APCI-FT-Orbitrap MS. Analysis revealed that the EA subfraction primarily contained aromatic dimers (C 19 –C 20 ) and trimers (C 17 –C 13 ), while the MeOH subfraction was rich in oxygenated aliphatic monomers (C 8 –C 16 ) likely derived from sugar dehydration products. The resulting fractions were further separated via preparatory HPLC. Fifty-five candidate molecular structures were proposed based on the Orbitrap MS data, supported by UV-fluorescence, FTIR, and NMR results. This fractionation strategy defined four distinct subfractions, enabling the proposal of surrogate molecular structures and advancing the molecular-level understanding of the HMW-PL fraction in the pyrolysis bio-oil.

High-Molecular-Weight PL↗
DOE OSTI2026

Optimal Design and Techno-Economic Analysis of 3D-Printed, Intensified Packings for Absorbers and Strippers in Solvent-Based CO 2 Capture

A potential technology for the CO 2 absorption process is utilizing intensified structured packing with embedded cooling/heating channels for continuous heat exchange, which can overcome limitations of discrete methods, such as discrete intercooling and centralized reboilers, to aid in reducing energy consumption and decreasing costs. This work investigates the modeling of intensified packing (IP) for the stripper tower, extending on previous work for the absorber, which distributes heat internally within the column, improving the thermodynamics for the solvent regeneration process. The model includes submodels for steam turbine extraction to produce steam at various qualities as well as a surrogate model for calculating steam enthalpy. A cost model for a plant-scale absorption capture process was developed, allowing for the design of the plant to be optimized, subject to minimizing capture cost using two different power plant flue gas sources. In this optimization, the placement of IP in both towers is optimized to balance the trade-off between enhanced heat transfer and reduced mass transfer volume. For natural gas combined cycle flue gas, the standard process configuration had a minimum cost of $\$$65.40/tonne CO 2 , and considering IP, the minimum capture cost is reduced to $\$$62.73/tonne, with utilization in the stripper column, which reduces yearly costs by up to $\$$2.67 MM/yr. Cooling the absorber through IP, or intercoolers, was only found to be beneficial at higher capture rates, with IP in both towers having a cost of capture of $\$$68.08/tonne at 99.9% capture, a reduction of $\$$12.64/tonne when using only intercoolers at the same capture rate. When capturing from pulverized-coal power plants, the minimum cost of capture when using IP in both towers is $\$$44.18/tonne (at 97% capture), while the standard configuration with and without intercoolers was $\$$45.69 and $\$$47.22 per tonne, respectively. This results in a reduction in yearly costs of $\$$16.98 MM/yr from the base-case configuration. At this higher CO 2 concentration, cooling in the absorber from the IP becomes extremely beneficial, reducing energy consumption by up to 6%.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2026

Spatial Optimization of Multiscale Biorefinery Deployment for a Diversified Bioeconomy in the United States

Strategic biorefinery siting is critical for a diversified bioeconomy, yet industry, policy, and research often focus on either large-scale biofuel plants or smaller-scale specialty bioproduct facilities, with limited coordination across scales. We address this gap by modeling biorefinery deployment spanning a 28-fold difference in capacity. We developed an open-source, spatially explicit framework integrating techno-economic analysis with logistics and refinery cost surrogate models to evaluate multiscale miscanthus-derived biorefineries across the rainfed U.S. for the production of ethanol, succinic acid, lactic acid, potassium sorbate, and acrylic acid. Overall costs change little as feedstock density increases, while transport distances decrease by ∼30 to 67% (∼100 km) and siting flexibility improves. Specifically, a 5-fold feedstock density increase (2% to 10% of suitable land) reduces minimum selling prices by <10% (e.g., 0.27 USD·gal –1 for ethanol). This limited economic sensitivity suggests dense planting is not required for competitive deployment, particularly for smaller-scale facilities. Representing collection areas as irregular rather than circular expands the feasible space under low-density scenarios. While large-scale refineries anchor regional supply chains, smaller facilities retain spatial flexibility even when large refineries are established. These findings highlight the importance of spatial representation and multiscale coordination for robust, regionally tailored biomanufacturing networks to advance renewable carbon integration without extensive land conversion.

biorefinery siting↗
DOE OSTI2026

Time-Resolved Neutron Imaging for Hydrogen Uptake in Subsurface Lithologies

Geologic hydrogen production and underground storage are increasingly important for meeting rising energy demands while providing clean-combustion advantages. However, hydrogen’s high diffusivity and propensity for leakage through porous media necessitate direct evaluation of its transport behavior in subsurface materials. Whereas X-ray microcomputed tomography (μCT) studies often employ contrast agents or surrogate gases, this study leverages neutron transmission radiography/CT to observe hydrogen migration in situ. This work represents the first demonstration of real-time neutron radiography of hydrogen migration in reservoir and caprock lithologies. Cylindrical cores of Indiana limestone, Amherst Gray sandstone, and Tumey shale were subjected to constant-pressure hydrogen charging and scanned in real time using high-resolution neutron radiography. Results indicate immediate hydrogen infiltration in sandstone and limestone, with homogeneous distribution detected throughout their pore structure. In contrast, hydrogen remained largely absent from fine-grained shale under the same pressure, except in an apparently localized fracture zone, where neutron signatures confirmed the presence of hydrogen. Subsequent neutron CT of the sandstone sample, using image subtraction against an uncharged reference, corroborated hydrogen distribution patterns. Even under lowpressure, single-phase conditions, distinct neutron imaging signatures of hydrogen were achieved. These preliminary findings underscore the potential of neutron imaging for advancing subsurface hydrogen migration research.

08 HYDROGEN↗
DOE OSTI2021

Dynamic Process Intensification via Data-Driven Dynamic Optimization: Concept and Application to Ternary Distillation

Process intensification is a design philosophy aimed at making chemical processes safer and more efficient. Its implementation often results in significant modifications to the design and structure of the process, with several conventional unit operations occurring in the same physical device. Traditionally, process intensification has focused on steady-state operation. In our previous works, we introduced dynamic process intensification (DPI) as a new intensification paradigm based on operational changes for conventional or intensified units. DPI is predicated on switching operation between two auxiliary steady states selected via a steady-state optimization calculation that ensures that the system generates, on average and over time, the same products as in nominal steady-state operation, but with favorable economics. This paper extends the DPI concept and introduces a novel dynamic optimization-based DPI strategy (Do-DPI) that involves imposing a true cyclic operation rather than switching between two discrete states. We discuss its implementation using surrogate dynamic models learned via system identification. Here, an extensive case study concerning a ternary distillation column separating a canonical hydrocarbon mixture shows that Do-DPI can reduce energy use by more than 4% relative to steady-state operation, with no significant deviations in product quality and production rate.

42 ENGINEERING↗
DOE OSTI2023

Optimization of Operating Profit for the FEED of the PZAS Process for CO 2 Capture on a 460 MW NGCC

A rating model of PZAS (Piperazine with the Advanced Stripper) for a 460 MW natural gas combined cycle was developed from vendor-provided equipment performance data. Surrogate rating models were built and used to optimize variable profit of the system subject to natural gas and electricity price at a fixed value for CO 2 of $\$80$/tonne. Several process constraints were considered between ambient temperatures of 4.4 and 40.5 °C. Lower lean loading resulted in lower reboiler heat duty of about 2.2 GJ/tonne. Lean loading at 0.2 mol/equiv N was sufficient at an ambient temperature of 4.4 °C to maximize variable profit. Solvent precipitation was avoided even at low lean loading (0.18 mol/mol) in the absence of a trim cooler for the lean solvent between the absorber and the cold cross exchanger. Optimal CO 2 removal was always higher than the design case removal of 90% and achieved a peak of 93.6% for 4.4 ºC ambient temperature. Lean solvent rate was a significant driver of profitability. The maximum capacity of the compressor was a significant constraint on profitability. Increasing compressor capacity by 20–30% could increase variable profit by about 21% in the case of 0.18 lean loading at 4.4 °C ambient temperature. Furthermore, this increase in profit was lower at higher ambient temperature and higher lean loading. The breakeven gas price was $\$4.6$/MMBtu at high lean loading of 0.22 mol/mol. Below this value, profit was maximized by increasing the boiler heat rate. Above this value, profit could not be increased by burning additional natural gas, requiring a reduction in boiler heat rate and consequently, specific heat duty. At lower lean loading (0.2, 0.18 mol/mol), this transition in heat duty was not observed due to the lower heat duty. As the ambient temperature increased, a similar trend in heat duty was observed at 0.22 lean loading, but the transition to lower heat duty occurred earlier at $\$4$/MMBtu. This was because of the lower CO 2 production at higher ambient temperature, making the process unprofitable at a gas price higher than $\$3$/MMBtu unless the heat duty of the stripper and natural gas boiler is steeply decreased.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Kinetics and Mechanism of Ce(IV) Phase Transfer by the Neutral Extractants Tributyl Phosphate and N,N -Di(2-ethylhexyl)isobutyramide

Tributyl phosphate and N,N-di(2-ethylhexyl)isobutyramide (DEHiBA) are uranium-selective extractants that could be used to recover low-enriched uranium from commercial used nuclear fuel. The economic viability of liquid-liquid extraction processes for chemical separations depends on both thermodynamic and kinetic considerations. Here we used microfluidic droplet extraction to measure interfacial phase transfer rate constants for the extraction and stripping of Ce(IV), a non-radioactive actinide surrogate. The Damkohler numbers for each system were calculated and the phase transfer processes were determined to be diffusion-limited under all conditions, contrary to prior studies using constant interface stirred cells and single drop methods. A well-extracted 2:1 DEHiBA/Ce(IV) complex in the organic phase was determined from batch distribution studies, suggesting a different extraction mechanism for Ce(IV) compared with poorly extracted Pu(IV). Finally, phase disengagement rates were found to be rapid in both systems, in agreement with other studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Thermodynamics of CeSiO 4 : Implications for Actinide Orthosilicates

Zircon (ZrSiO 4 : I4 1 /amd) can accommodate actinides, such as thorium, uranium, and plutonium. The zircon structure has been determined for several of the end member compositions of other actinides, such as plutonium and neptunium. However, the thermodynamic properties of these actinide zircon structure-types are largely unknown due to the difficulties in synthesizing these materials and handling transuranium actinides. Thus, we have completed a thermodynamic study of cerium orthosilicate, stetindite (CeSiO 4 ), a surrogate of PuSiO 4 . For the first time, the standard enthalpy of formation of CeSiO 4 was obtained by high temperature oxide melt solution calorimetry to be -1971.9 ± 3.6 kJ/mol. Stetindite is energetically metastable with respect to CeO 2 and SiO 2 by 27.5 ± 3.1 kJ/mol. The metastability explains the rarity of the natural occurrence of stetindite and the difficulty of its synthesis. Applying the obtained enthalpy of formation of CeSiO 4 from this work, along with those previously reported for USiO 4 and ThSiO 4 , we developed an empirical energetic relation for actinide orthosilicates. Here, the predicted enthalpies of formation of AnSiO 4 are then made with a discussion of future strategies to efficiently immobilize Pu or minor actinides in the zircon structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Pronounced Pressure Dependence of Electronic Transitions for Americium Compared to Isomorphous Neodymium and Samarium Mellitates

The mellitate ion is relevant in spent nuclear fuel processing and is utilized as a surrogate for studying the interactions of f elements with humic acids. A wealth of different coordination modes gives the potential for diverse structural chemistry across the actinide series. In this study, an americium mellitate, 243 Am 2 [(C 6 (COO – ) 6 ](H 2 O) 8 ·2H 2 O (1-Am), has been synthesized and characterized using structural analysis and spectroscopy at ambient and elevated pressures. 1-Am was then compared to isomorphous neodymium (1-Nd) and samarium (1-Sm) mellitates via bond-length analysis and pressure dependence of their Laporte-forbidden f → f transitions. Results show that the pressure dependence of the f → f transitions of 1-Am is significantly greater than that observed in 1-Nd and 1-Sm, with average shifts of 21.4, 4.7, and 3.6 cm –1 /GPa, respectively. Finally, this greater shift found in 1-Am shows further evidence that the 5f orbitals are more affected than the 4f orbitals when pressure is applied to isostructural compounds.

Actinides↗
DOE OSTI2023

Elucidating Actinide–Pertechnetate and Actinide–Perrhenate Bonding via a Family of Th–TcO 4 and Th–ReO 4 Frameworks and Solutions

Technetium-99, a β-emitter produced from 235 U fission, poses a challenge for the nuclear industry due to co-extraction of pertechnetate (TcO 4 – ) with the actinides (An) during nuclear fuel reprocessing. Previous studies suggested that direct coordination of pertechnetate with An plays an important role in the coextraction process. However, few studies have provided direct evidence for An–TcO 4 – bonding in the solid state, and even fewer in solution. The present study describes synthesis and structural elucidation of a family of thorium(IV)-pertechnetate/perrhenate (ReO 4 – , nonradioactive surrogate) compounds, which is obtained by dissolution of thorium oxyhydroxide in perrhenic/pertechnic acid followed by crystallization, with or without heating. For reaction ratios of 3:1, 4:1, and 6:1 MO 4 – /Th(IV) (M = Tc, Re), the crystallized compounds reflect the same ratio, suggesting facile and flexible coordination. Furthermore, nine structures reveal 1-dimensional and 2-dimensional frameworks with varying topologies. While a multitude of compounds isolated from 4:1 (and 6:1) reaction solutions feature Th monomers linked by MO 4 – , the 3:1 reaction solution yielded the well-known dihydroxide-bridged thorium dimer, linked, and capped by MO 4 – . Density functional theory calculations on ReO 4 – /TcO 4 – isomorphs suggest similar bonding characteristics in the solid state, but experimental solution characterization noted differences. Specifically, small-angle X-ray scattering studies suggest the bonding of Th–TcO 4 – persists in solution, while Th–ReO 4 – bonding is less apparent.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Post-Mortem Characterization of Cerium Speciation in Molten Calcium Chloride

Abstract Advancing radiochemistry and nuclear materials science requires understanding actinide interactions with molten salts, which are used in next-generation nuclear reactors and for processing of actinides to recover useful fissile material. Understanding chemical interactions of actinides with molten salts has been limited by challenges in developing spectroscopic and X-ray techniques that are compatible with the high temperatures necessary to study molten salts. In this work, interactions of CeO2 (serving as a nonradioactive surrogate for uranium and plutonium) with CaCl2 are characterized following heating. Scanning electron microscopy indicates CeO2 morphological changes from small (<1 μm) particles to 3–5 μm sheets. Powder X-ray diffraction and infrared and Raman spectroscopies show the formation of CeOCl at higher (850–1050 °C) temperatures. In the absence of a chemical reducing agent, it was found that a high-temperature, low-oxygen environment is the key to the formation of oxychloride and that oxychloride formation is inhibited by annealing the CeO2 starting material. Lastly, thermal analysis revealed lowering of the melting point of CaCl2 after heating with CeO2. In all, this work identifies applicable spectroscopic techniques to target studies of heavy elements in molten salt environments and highlights the relationship between chemical speciation and melting behavior, a key thermophysical property.

Kelly, Sheridon N. [Lawrence Livermore National La↗